orcakit-sdk 0.1.3

OrcaKit SDK - Common utilities and adapters for AI Agent development based on LangGraph

OrcaKit SDK

A public SDK package for AI Agent development based on LangGraph, providing common utilities, MCP adapters, and compatible LLM service support.

Features

• 🔧 MCP Adapter: Integrated Model Context Protocol (MCP) client with multi-server configuration support
• 🤖 Compatible Models: Support for OpenAI-compatible LLM services (e.g., DeepSeek)
• 🛠️ Utility Functions: Message handling, model loading, and other common utilities
• 📦 Lightweight: Minimal core dependencies for easy integration

Installation

pip install orcakit-sdk

Or using uv:

uv add orcakit-sdk

Quick Start

Using OpenAI-Compatible Models

from orcakit_sdk import create_compatible_openai_client

# Create client (requires OPENAI_API_KEY and OPENAI_BASE_URL environment variables)
client = create_compatible_openai_client(model_name="gpt-4")

# Or use default model (read from OPENAI_MODEL_NAME environment variable)
client = create_compatible_openai_client()

Using MCP Adapter

import asyncio
from orcakit_sdk import get_mcp_client, get_mcp_tools

async def main():
    # MCP server configuration (JSON format)
    server_configs = '''
    {
        "mcpServers": {
            "filesystem": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/allowed/files"]
            }
        }
    }
    '''
    
    # Get MCP client
    client = await get_mcp_client(server_configs)
    
    # Get available tools
    tools = await get_mcp_tools(server_configs)
    print(f"Loaded {len(tools)} tools")

asyncio.run(main())

Loading Chat Models

from orcakit_sdk import load_chat_model

# Load model from fully qualified name
model = load_chat_model("openai/gpt-4")

# Or use OpenAI-compatible model
model = load_chat_model("compatible_openai/deepseek-chat")

Processing Message Content

from orcakit_sdk import get_message_text
from langchain_core.messages import HumanMessage

msg = HumanMessage(content="Hello, world!")
text = get_message_text(msg)
print(text)  # Output: Hello, world!

Environment Variables

The SDK supports the following environment variable configurations:

• OPENAI_API_KEY: OpenAI API key
• OPENAI_BASE_URL: OpenAI API base URL (for compatible services)
• OPENAI_MODEL_NAME: Default model name

Example .env file:

OPENAI_API_KEY=sk-xxx
OPENAI_BASE_URL=https://api.deepseek.com/v1
OPENAI_MODEL_NAME=deepseek-chat

API Reference

MCP Adapter

get_mcp_client(server_configs: str) -> MultiServerMCPClient | None

Get or initialize the global MCP client.

Parameters:

• server_configs: JSON-formatted server configuration string

Returns:

• MultiServerMCPClient instance or None (if initialization fails)

get_mcp_tools(server_configs: str) -> list[Callable[..., object]]

Get the list of tools provided by the MCP server.

Parameters:

• server_configs: JSON-formatted server configuration string

Returns:

• List of tool functions

clear_mcp_cache() -> None

Clear the MCP client and tools cache (mainly for testing).

Model Tools

create_compatible_openai_client(model_name: str | None = None) -> ChatOpenAI

Create an OpenAI-compatible chat model client.

Parameters:

• model_name: Model name (optional, defaults to environment variable)

Returns:

• ChatOpenAI client instance

load_chat_model(fully_specified_name: str) -> BaseChatModel

Load a chat model from a fully qualified name.

Parameters:

• fully_specified_name: String in the format provider/model

Returns:

• BaseChatModel instance

Utility Functions

get_message_text(msg: BaseMessage) -> str

Extract text content from a message object.

Parameters:

• msg: LangChain message object

Returns:

• Extracted text content

Development

Install Development Dependencies

make install-dev

Run Tests

make test

Code Formatting

make format

Code Linting

make lint

Project Structure

orcakit-sdk/
├── src/
│   └── orcakit_sdk/
│       ├── __init__.py          # Package entry point
│       ├── mcp_adapter.py       # MCP adapter
│       ├── model.py             # Model utilities
│       └── utils.py             # Utility functions
├── tests/
│   ├── unit_tests/
│   │   ├── test_utils.py
│   │   └── test_model.py
│   └── integration_tests/
├── pyproject.toml               # Project configuration
├── Makefile                     # Development commands
└── README.md                    # Project documentation

Dependencies

Core dependencies:

• langgraph >= 0.6.6: LangGraph framework
• langchain >= 0.2.14: LangChain core library
• langchain-openai >= 0.1.22: OpenAI integration
• langchain-mcp-adapters >= 0.1.9: MCP adapter
• python-dotenv >= 1.0.1: Environment variable management

License

MIT License

Contributing

Issues and Pull Requests are welcome!

Author

William Fu-Hinthorn ([e-mail])